Refactor variable value retrieval and timing in flow models

Replaces use of get_variable_values with get_values for direct variable access in flow model classes, improving reliability and type safety. Adds solve_time_start initialization for accurate timing in all k-cycle model classes. Updates variable name parsing and retrieval logic in SolverWrapper to be more robust and removes internal prefix collision tracking, making prefix management the caller's responsibility. Also updates cycles_demo.py to activate more test cases and adjusts optimization options.

Author: alexandrutomescu

examples/cycles_demo.py

@@ -28,8 +28,8 @@ def test_min_flow_decomp(filename: str):
         optimization_options={
             "optimize_with_safe_sequences": True, # set to false to deactivate the safe sequences optimization
             "optimize_with_safe_sequences_allow_geq_constraints": True,
-            "optimize_with_safe_sequences_fix_via_bounds": True,
-            "optimize_with_safe_sequences_fix_zero_edges": False,
+            "optimize_with_safe_sequences_fix_via_bounds": False,
+            "optimize_with_safe_sequences_fix_zero_edges": True,
         },
         solver_options={
             "external_solver": "highs", # we can try also "highs" at some point
@@ -152,10 +152,10 @@ def process_solution(model):
     print("avg_size_of_non_trivial_SCC:", solve_statistics['avg_size_of_non_trivial_SCC']) # size = number of edges
 
 def main():
-    # test_min_flow_decomp(filename = "tests/cyclic_graphs/gt3.kmer15.(130000.132000).V23.E32.cyc100.graph")
+    test_min_flow_decomp(filename = "tests/cyclic_graphs/gt3.kmer15.(130000.132000).V23.E32.cyc100.graph")
     test_min_flow_decomp(filename = "tests/cyclic_graphs/gt5.kmer27.(1300000.1400000).V809.E1091.mincyc1000.graph")
-    # test_least_abs_errors(filename = "tests/cyclic_graphs/gt5.kmer27.(655000.660000).V18.E27.mincyc4.e0.75.graph")
-    # test_min_path_error(filename = "tests/cyclic_graphs/gt5.kmer27.(655000.660000).V18.E27.mincyc4.e0.75.graph")
+    test_least_abs_errors(filename = "tests/cyclic_graphs/gt5.kmer27.(655000.660000).V18.E27.mincyc4.e0.75.graph")
+    test_min_path_error(filename = "tests/cyclic_graphs/gt5.kmer27.(655000.660000).V18.E27.mincyc4.e0.75.graph")
 
 if __name__ == "__main__":
     # Configure logging

flowpaths/abstractwalkmodeldigraph.py

@@ -164,7 +164,10 @@ def __init__(
         )
 
         self._is_solved = False
-                
+
+        if not hasattr(self, "solve_time_start") or self.solve_time_start is None:
+            self.solve_time_start = time.perf_counter()
+
     def create_solver_and_walks(self):
         """
         Creates a solver instance and encodes the walks in the graph.
@@ -611,6 +614,7 @@ def solve(self) -> bool:
         start_time = time.perf_counter()
         self.solver.optimize()
         self.solve_statistics[f"solve_time_ilp"] = time.perf_counter() - start_time
+        self.solve_statistics[f"solve_time"] = time.perf_counter() - self.solve_time_start
         self.solve_statistics[f"model_status"] = self.solver.get_model_status()
         self.solve_statistics[f"number_of_nontrivial_SCCs"] = self.G.get_number_of_nontrivial_SCCs()
         self.solve_statistics[f"avg_size_of_non_trivial_SCC"] = self.G.get_avg_size_of_non_trivial_SCC()
@@ -672,9 +676,7 @@ def get_solution_walks(self) -> list:
         """
 
         if self.edge_vars_sol == {}:
-            self.edge_vars_sol = self.solver.get_variable_values(
-                "edge", [str, str, int]
-            )
+            self.edge_vars_sol = self.solver.get_values(self.edge_vars)
         # utils.logger.debug(f"{__name__}: Getting solution walks with self.edge_vars_sol = {self.edge_vars_sol}")
 
         # self.distance_vars_sol = self.solver.get_variable_values("distance", [str, int])

flowpaths/kflowdecompcycles.py

@@ -4,7 +4,7 @@
 import flowpaths.utils as utils
 import flowpaths.nodeexpandeddigraph as nedg
 import copy
-
+import time
 
 class kFlowDecompCycles(walkmodel.AbstractWalkModelDiGraph):
     def __init__(
@@ -161,6 +161,7 @@ def __init__(
         self._lowerbound_k = None
 
         self.solve_statistics = {}
+        self.solve_time_start = time.perf_counter()
 
         self.optimization_options["trusted_edges_for_safety"] = self.G.get_non_zero_flow_edges(flow_attr=self.flow_attr, edges_to_ignore=self.edges_to_ignore)
 
@@ -202,9 +203,7 @@ def __init__(
 
     def _encode_flow_decomposition(self):
 
-        # print("edge_upper_bounds", self.edge_upper_bounds)
         # pi vars 
-        # edge_ubs = [self.edge_upper_bounds[(u, v)] for (u, v, i) in self.edge_indexes]
         self.pi_vars = self.solver.add_variables(
             self.edge_indexes,
             name_prefix="pi",
@@ -326,7 +325,7 @@ def get_solution(self, remove_empty_walks=True):
 
         self.check_is_solved()
 
-        weights_sol_dict = self.solver.get_variable_values("weights", [int])
+        weights_sol_dict = self.solver.get_values(self.path_weights_vars)
 
         utils.logger.debug(f"{__name__}: weights_sol_dict = {weights_sol_dict}")
 

flowpaths/kleastabserrorscycles.py

@@ -5,6 +5,7 @@
 import flowpaths.nodeexpandeddigraph as nedg
 import copy
 import numpy as np
+import time
 
 class kLeastAbsErrorsCycles(walkmodel.AbstractWalkModelDiGraph):
     def __init__(
@@ -216,6 +217,7 @@ def __init__(
         self._lowerbound_k = None
 
         self.solve_statistics = {}
+        self.solve_time_start = time.perf_counter()
 
         # If we get subset constraints, and the coverage fraction is 1
         # then we know their edges must appear in the solution, so we add their edges to the trusted edges for safety
@@ -371,7 +373,7 @@ def get_solution(self, remove_empty_walks=True):
 
         self.check_is_solved()
 
-        weights_sol_dict = self.solver.get_variable_values("weights", [int])
+        weights_sol_dict = self.solver.get_values(self.path_weights_vars)
 
         utils.logger.debug(f"{__name__}: weights_sol_dict = {weights_sol_dict}")
 
@@ -383,7 +385,7 @@ def get_solution(self, remove_empty_walks=True):
             )
             for i in range(self.k)
         ]
-        self.edge_errors_sol = self.solver.get_variable_values("ee", [str, str])
+        self.edge_errors_sol = self.solver.get_values(self.edge_errors_vars)
         for (u,v) in self.edge_indexes_basic:
             self.edge_errors_sol[(u,v)] = round(self.edge_errors_sol[(u,v)]) if self.weight_type == int else float(self.edge_errors_sol[(u,v)])
 

flowpaths/kminpatherrorcycles.py

@@ -5,7 +5,7 @@
 import flowpaths.nodeexpandeddigraph as nedg
 import copy
 import numpy as np
-
+import time
 
 class kMinPathErrorCycles(walkmodel.AbstractWalkModelDiGraph):
     def __init__(
@@ -197,7 +197,8 @@ def __init__(
         self._lowerbound_k = None
 
         self.solve_statistics = {}
-        
+        self.solve_time_start = time.perf_counter()
+
         if trusted_edges_for_safety_percentile is not None:
             # Select edges where the flow_attr value is >= trusted_edges_for_safety_percentile (using self.G)
             flow_values = [self.G.edges[edge][flow_attr] for edge in self.G.edges() if flow_attr in self.G.edges[edge]]
@@ -399,7 +400,7 @@ def get_solution(self, remove_empty_walks=True):
 
         self.check_is_solved()
 
-        weights_sol_dict = self.solver.get_variable_values("weights", [int])
+        weights_sol_dict = self.solver.get_values(self.path_weights_vars)
         self.path_weights_sol = [
             (
                 round(weights_sol_dict[i])
@@ -408,7 +409,7 @@ def get_solution(self, remove_empty_walks=True):
             )
             for i in range(self.k)
         ]
-        slacks_sol_dict = self.solver.get_variable_values("slack", [int])
+        slacks_sol_dict = self.solver.get_values(self.path_slacks_vars)
         self.path_slacks_sol = [
             (
                 round(slacks_sol_dict[i])

flowpaths/kpathcovercycles.py

@@ -4,6 +4,7 @@
 import flowpaths.utils as utils
 import flowpaths.nodeexpandeddigraph as nedg
 from copy import deepcopy
+import time
 
 class kPathCoverCycles(walkmodel.AbstractWalkModelDiGraph):
     def __init__(
@@ -128,6 +129,7 @@ def __init__(
         self._lowerbound_k = None
 
         self.solve_statistics = {}
+        self.solve_time_start = time.perf_counter()
         self.optimization_options = optimization_options.copy() if optimization_options else {}
         self.optimization_options["trusted_edges_for_safety"] = set(e for e in self.G.edges() if e not in self.edges_to_ignore)